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Comment on: Childhood cancer and exposure to corona ions from power lines: an epidemiological study
This content has been downloaded from IOPscience. Please scroll down to see the full text. 2015 J. Radiol. Prot. 35 481 (http://iopscience.iop.org/0952-4746/35/2/481) View the table of contents for this issue, or go to the journal homepage for more
Download details: IP Address: 131.94.16.10 This content was downloaded on 01/09/2015 at 05:54
Please note that terms and conditions apply.
Society for Radiological Protection J. Radiol. Prot. 35 (2015) 481–483
Journal of Radiological Protection doi:10.1088/0952-4746/35/2/481
Letter to the Editor
Comment on: Childhood cancer and exposure to corona ions from power lines: an epidemiological study
Swanson et al [1] tested the hypothesis that the atmospheric ions produced by corona discharges could increase the retention of pollutants in the airways and hence cause disease [2]. They concluded that their data do not support the ‘corona ion hypothesis’ and they said of the model used to assess exposure: The ions produced by power lines can sometimes be detected kilometres away, but measurements made by ourselves and others lead us to model the observed average variation of ions with distance from the power line, when the wind is transverse to the line, as shown in figure 2. We know that the distance variation is also affected by other factors, such as environmental conditions, but we are unable to model these. The distribution from their figure 2 ‘distance weighting term for the variation of corona ions from a power line’, which assigns zero exposure outside of 600 m is reproduced on the figure below. An alternative model which does take account of environmental conditions is presented in this note. For comparison, the resulting distributions are superimposed on that of Swanson et al. The late Dr Pasquill distilled a mass of experimental data on atmospheric dispersion into a widely used procedure for estimating pollution concentrations down wind of an elevated pollution source [3, 4] and it is applied here to model the dispersion of corona ions. A corona point emitting Q ions s−1 into a wind of speed, u m s−1, at height, Hi, generates a down wind ‘Gaussian Plume’ with a ground level concentration, Ci(Q ) m−3, of: 2 2 ⎛Q ⎞ 1 1⎛ y ⎞ 1⎛H ⎞ C exp − ⎜ i ⎟ exp − ⎜ ⎟ (1) i (Q )=⎜ ⎟ ⎝ u ⎠ πσzσy 2 ⎝ σy ⎠ 2 ⎝ σz ⎠
where σz and σy (m) are the vertical (z) and crosswind (y) standard deviations of the concentration distribution. They are empirical functions of the distance down-wind and of the atmospheric conditions, which Pasquill assigned to six classes ranging from A (extremely unstable) to F (moderately stable). For illustration, Class D, which applies to a ‘neutral’ atmosphere is used here [4], making σz = 21 m and σy = 43 m at 600 m down-wind. The resulting, normalised, down-wind (y = 0), distribution from a point source at the typical middle conductor height of 19.85 m is plotted on figure 1. It peaks at 355 m falls to 73% of its peak at 600 m and 40% at a kilometre. This provides strong support for the observation by Swanson and his colleagues that ions can sometimes be detected kilometres away—but not for their cut off at 600 m. Because of the narrowness of the ion plume, exposure from a point source, such as a defective conductor spacer, is a hit and miss affair and a swing in wind direction of 20 degrees can make the plume miss an observer entirely. 0952-4746/15/020481+3$33.00 © 2015 IOP Publishing Ltd Printed in the UK
481
Letter to the Editor
J. Radiol. Prot. 35 (2015) 481
Normalised Concentration
1.2 1
3
1
0.8 0.6
2
0.4 0.2 0 0
200
–0.2
400
600
800
1000
1200
Down wind distance, x, m
Figure 1. Normalised corona ion density plots. 1: figure 2 from Swanson et al paper. 2: down-wind distribution from point source at 19.85 m. 3: continuous corona sources at 12, 19.85 and 27.6 m in cross wind.
Pasquill’s model can, however, be extended to model emission from a line source. In a cross-wind, a long conductor which is emitting q ions m−1 s−1 generates a down wind concentration, Cni(q ) ions m−3, given by: ∞
2 ⎛q⎞ ⎛2⎞ 1 1⎛H ⎞ (2) C Ci(q )dy = ⎜ ⎟√⎜ ⎟ exp − ⎜ i ⎟ ni(q ) = ⎝ u ⎠ ⎝ π ⎠ σz 2 ⎝ σz ⎠
∫
−∞
(At a distance of 600 m, 95% of this value would be generated by a conductor of length 170 m, which is less than the typical distance between pylons of about 300 m.) Assuming identical corona generation on all three phases, a normalised concentration distribution for the most corona prone 400 kV line design [1] is plotted on figure 1. It peaks at 500 m and has only fallen to 84% of its maximum at a distance of 1000 m—in stark contrast to Swanson and colleagues’ observation that their model ‘assigns zero exposure outside 600 m.’ If corona ions did have health effects, one would therefore expect them to be manifest at distances from 500 to 1000 m from the line. Bunch et al [5] studied the incidence of childhood cancer in relation to distance at birth from high-voltage power lines over the period 1962–2008 and their aggregate data for distances of 600–1000 m provide no hint of a risk. The estimated relative risks were: for leukaemia, 0.99 (0.88–1.11), for CNS/brain tumours 0.98 (0.86–1.12) and for other tumours 0.99 (0.90–1.09). To conclude, this application of Pasquill’s model raises important questions regarding the validity of the assumptions made by Swanson and his colleagues whilst, at the same time, providing strong support for their conclusion that the data do not support the ‘corona ion hypothesis’. References [1] Swanson J, Bunch K J, Vincent T J and Murphy M F G 2014 Childhood cancer and exposure to corona ions from power lines: an epidemiological test J. Radiol. Prot. 34 873–89 [2] Advisory Group on non-ionising radiation (A.G.N.I.R) 2004 Particle deposition in the vicinity of power lines and possible effects on health Documents of the NRPB vol. 15 (Chilton: National Radiological Protection Board) 482
Letter to the Editor
J. Radiol. Prot. 35 (2015) 481
[3] Turner D B 1970 Workbook of atmospheric dispersion estimates U S Environmental Protection Agency, Office of Air Programs (Research Triangle Park, North Carolina) [4] Cooper C D and Alley F C 2011 Air Pollution Control: a Design Approach 4th edn (Long Grove, IL: Waveland Press) pp 662–3 [5] Bunch K J, Keegan T J, Swanson J, Vincent T J and Murphy M F G 2014 Residential distance at birth from overhead high-voltage power lines: childhood cancer risk in Britain 1962–2008 Br. J. Cancer 110 1402–8
David Jeffers1 Meadlands, Three Gates Lane, Haslemere GU27 2LD, UK E-mail: [email protected]
1
No current affiliation but late (retired 1999) of the National Grid Company. 483
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Comment on: Childhood cancer and exposure to corona ions from power lines: an epidemiological study
This content has been downloaded from IOPscience. Please scroll down to see the full text. 2015 J. Radiol. Prot. 35 481 (http://iopscience.iop.org/0952-4746/35/2/481) View the table of contents for this issue, or go to the journal homepage for more
Download details: IP Address: 131.94.16.10 This content was downloaded on 01/09/2015 at 05:54
Please note that terms and conditions apply.
Society for Radiological Protection J. Radiol. Prot. 35 (2015) 481–483
Journal of Radiological Protection doi:10.1088/0952-4746/35/2/481
Letter to the Editor
Comment on: Childhood cancer and exposure to corona ions from power lines: an epidemiological study
Swanson et al [1] tested the hypothesis that the atmospheric ions produced by corona discharges could increase the retention of pollutants in the airways and hence cause disease [2]. They concluded that their data do not support the ‘corona ion hypothesis’ and they said of the model used to assess exposure: The ions produced by power lines can sometimes be detected kilometres away, but measurements made by ourselves and others lead us to model the observed average variation of ions with distance from the power line, when the wind is transverse to the line, as shown in figure 2. We know that the distance variation is also affected by other factors, such as environmental conditions, but we are unable to model these. The distribution from their figure 2 ‘distance weighting term for the variation of corona ions from a power line’, which assigns zero exposure outside of 600 m is reproduced on the figure below. An alternative model which does take account of environmental conditions is presented in this note. For comparison, the resulting distributions are superimposed on that of Swanson et al. The late Dr Pasquill distilled a mass of experimental data on atmospheric dispersion into a widely used procedure for estimating pollution concentrations down wind of an elevated pollution source [3, 4] and it is applied here to model the dispersion of corona ions. A corona point emitting Q ions s−1 into a wind of speed, u m s−1, at height, Hi, generates a down wind ‘Gaussian Plume’ with a ground level concentration, Ci(Q ) m−3, of: 2 2 ⎛Q ⎞ 1 1⎛ y ⎞ 1⎛H ⎞ C exp − ⎜ i ⎟ exp − ⎜ ⎟ (1) i (Q )=⎜ ⎟ ⎝ u ⎠ πσzσy 2 ⎝ σy ⎠ 2 ⎝ σz ⎠
where σz and σy (m) are the vertical (z) and crosswind (y) standard deviations of the concentration distribution. They are empirical functions of the distance down-wind and of the atmospheric conditions, which Pasquill assigned to six classes ranging from A (extremely unstable) to F (moderately stable). For illustration, Class D, which applies to a ‘neutral’ atmosphere is used here [4], making σz = 21 m and σy = 43 m at 600 m down-wind. The resulting, normalised, down-wind (y = 0), distribution from a point source at the typical middle conductor height of 19.85 m is plotted on figure 1. It peaks at 355 m falls to 73% of its peak at 600 m and 40% at a kilometre. This provides strong support for the observation by Swanson and his colleagues that ions can sometimes be detected kilometres away—but not for their cut off at 600 m. Because of the narrowness of the ion plume, exposure from a point source, such as a defective conductor spacer, is a hit and miss affair and a swing in wind direction of 20 degrees can make the plume miss an observer entirely. 0952-4746/15/020481+3$33.00 © 2015 IOP Publishing Ltd Printed in the UK
481
Letter to the Editor
J. Radiol. Prot. 35 (2015) 481
Normalised Concentration
1.2 1
3
1
0.8 0.6
2
0.4 0.2 0 0
200
–0.2
400
600
800
1000
1200
Down wind distance, x, m
Figure 1. Normalised corona ion density plots. 1: figure 2 from Swanson et al paper. 2: down-wind distribution from point source at 19.85 m. 3: continuous corona sources at 12, 19.85 and 27.6 m in cross wind.
Pasquill’s model can, however, be extended to model emission from a line source. In a cross-wind, a long conductor which is emitting q ions m−1 s−1 generates a down wind concentration, Cni(q ) ions m−3, given by: ∞
2 ⎛q⎞ ⎛2⎞ 1 1⎛H ⎞ (2) C Ci(q )dy = ⎜ ⎟√⎜ ⎟ exp − ⎜ i ⎟ ni(q ) = ⎝ u ⎠ ⎝ π ⎠ σz 2 ⎝ σz ⎠
∫
−∞
(At a distance of 600 m, 95% of this value would be generated by a conductor of length 170 m, which is less than the typical distance between pylons of about 300 m.) Assuming identical corona generation on all three phases, a normalised concentration distribution for the most corona prone 400 kV line design [1] is plotted on figure 1. It peaks at 500 m and has only fallen to 84% of its maximum at a distance of 1000 m—in stark contrast to Swanson and colleagues’ observation that their model ‘assigns zero exposure outside 600 m.’ If corona ions did have health effects, one would therefore expect them to be manifest at distances from 500 to 1000 m from the line. Bunch et al [5] studied the incidence of childhood cancer in relation to distance at birth from high-voltage power lines over the period 1962–2008 and their aggregate data for distances of 600–1000 m provide no hint of a risk. The estimated relative risks were: for leukaemia, 0.99 (0.88–1.11), for CNS/brain tumours 0.98 (0.86–1.12) and for other tumours 0.99 (0.90–1.09). To conclude, this application of Pasquill’s model raises important questions regarding the validity of the assumptions made by Swanson and his colleagues whilst, at the same time, providing strong support for their conclusion that the data do not support the ‘corona ion hypothesis’. References [1] Swanson J, Bunch K J, Vincent T J and Murphy M F G 2014 Childhood cancer and exposure to corona ions from power lines: an epidemiological test J. Radiol. Prot. 34 873–89 [2] Advisory Group on non-ionising radiation (A.G.N.I.R) 2004 Particle deposition in the vicinity of power lines and possible effects on health Documents of the NRPB vol. 15 (Chilton: National Radiological Protection Board) 482
Letter to the Editor
J. Radiol. Prot. 35 (2015) 481
[3] Turner D B 1970 Workbook of atmospheric dispersion estimates U S Environmental Protection Agency, Office of Air Programs (Research Triangle Park, North Carolina) [4] Cooper C D and Alley F C 2011 Air Pollution Control: a Design Approach 4th edn (Long Grove, IL: Waveland Press) pp 662–3 [5] Bunch K J, Keegan T J, Swanson J, Vincent T J and Murphy M F G 2014 Residential distance at birth from overhead high-voltage power lines: childhood cancer risk in Britain 1962–2008 Br. J. Cancer 110 1402–8
David Jeffers1 Meadlands, Three Gates Lane, Haslemere GU27 2LD, UK E-mail: [email protected]
1
No current affiliation but late (retired 1999) of the National Grid Company. 483
